{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "96b560ef-5102-4444-ac02-7afdc1d85781",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w= [3.15636039] b= [0.04433569]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from sklearn.linear_model import LinearRegression,SGDRegressor\n",
    "x = np.array([[100],[113],[90],[89],[60],[70],[50],[45],[55],[78]])\n",
    "y = np.array([[301],[324],[285],[296],[200],[260],[300],[120],[180],[245]])\n",
    "model = SGDRegressor(loss='huber',max_iter=5000,random_state=42)\n",
    "model.fit(x,y.ravel())\n",
    "print(\"w=\",model.coef_,\"b=\",model.intercept_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "142976b2-31f5-4c45-892d-f135c650fd3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "y2 = model.predict(x)\n",
    "plt.xlabel('面积')\n",
    "plt.ylabel('售价')\n",
    "plt.rcParams['font.sans-serif']='Simhei'\n",
    "plt.axis([40,125,100,400])\n",
    "plt.scatter(x,y,s=60,c='k',marker='o')\n",
    "plt.plot(x,y2,'r-')\n",
    "plt.legend(['真实值','预测值'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c13c161-57f6-44e6-9c00-bc5ebe1ddac8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
